TY - JOUR
T1 - Stereo vision-based object recognition and manipulation by regions with convolutional neural network
AU - Du, Yi Chun
AU - Muslikhin, Muslikhin
AU - Hsieh, Tsung Han
AU - Wang, Ming Shyan
N1 - Funding Information:
Funding: This research was funded by Higher Education Sprout and Ministry of Science and Technology, the Ministry of Education, Taiwan and contract No. of MOST 108-2622-E-218-006-CC2, Ministry of Science and Technology.
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/2
Y1 - 2020/2
N2 - This paper develops a hybrid algorithm of adaptive network-based fuzzy inference system (ANFIS) and regions with convolutional neural network (R-CNN) for stereo vision-based object recognition and manipulation. The stereo camera at an eye-to-hand configuration firstly captures the image of the target object. Then, the shape, features, and centroid of the object are estimated. Similar pixels are segmented by the image segmentation method, and similar regions are merged through selective search. The eye-to-hand calibration is based on ANFIS to reduce computing burden. A six-degree-of-freedom (6-DOF) robot arm with a gripper will conduct experiments to demonstrate the effectiveness of the proposed system.
AB - This paper develops a hybrid algorithm of adaptive network-based fuzzy inference system (ANFIS) and regions with convolutional neural network (R-CNN) for stereo vision-based object recognition and manipulation. The stereo camera at an eye-to-hand configuration firstly captures the image of the target object. Then, the shape, features, and centroid of the object are estimated. Similar pixels are segmented by the image segmentation method, and similar regions are merged through selective search. The eye-to-hand calibration is based on ANFIS to reduce computing burden. A six-degree-of-freedom (6-DOF) robot arm with a gripper will conduct experiments to demonstrate the effectiveness of the proposed system.
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U2 - 10.3390/electronics9020210
DO - 10.3390/electronics9020210
M3 - Article
AN - SCOPUS:85078732803
VL - 9
JO - Electronics (Switzerland)
JF - Electronics (Switzerland)
SN - 2079-9292
IS - 2
M1 - 210
ER -